COVIDiag: a clinical CAD system to diagnose COVID-19 pneumonia based on CT findings.
| Publicado en: | European Radiology Vol. 31; no. 1; pp. 121 - 131 |
|---|---|
| Autores principales: | , , , |
| Formato: | Journal Article |
| Publicado: |
Springer Nature
2021
|
| Acceso en línea: | Ver este registro en EBSCOhost |
| fields | @attributes: recordID: 1 pdfLink: plink: https://search.ebscohost.com/login.aspx?direct=true&db=ccm&AN=147734713&site=ehost-live header: @attributes: shortDbName: ccm uiTerm: 147734713 longDbName: CINAHL Complete uiTag: AN controlInfo: bkinfo: dissinfo: jinfo: jid: 09387994 NPH jtl: European Radiology issn: 09387994 maglogo: N pubinfo: dt: 2021 vid: 31 iid: 1 pid: 237 pub: Springer Nature place: New York, New York artinfo: ui: 147734713 144866015 10.1007/s00330-020-07087-y 147734713 ppf: 121 ppct: 10 formats: fmt: – @attributes: type: T – @attributes: type: P tig: atl: COVIDiag: a clinical CAD system to diagnose COVID-19 pneumonia based on CT findings. aug: au: Abbasian Ardakani, Ali Acharya, U. Rajendra Habibollahi, Sina Mohammadi, Afshin affil: Medical Physics Department, School of Medicine, Iran University of Medical Sciences (IUMS), Tehran, Iran sug: pubtype: Academic Journal doctype: Journal Article ougenre: Article ab: language: English refInfo: holdings: @attributes: islocal: N |
|---|